Multi-spectral imaging involves capturing images of a scene or object over multiple discrete wavelength bands and extracting spectral content from that data. By leveraging known spectral absorption or emission features to identify materials, the technique can be used for everything from mapping rock types in geological formations to identifying blood oxygenation or cancer cells. The problem is that multi-spectral imagers have historically been large, expensive, sophisticated airborne or satellite-mounted instruments. Because each scene is captured in three-dimensions (x, y, λ), the resultant data cubes can be gigabytes in size, while only a fraction of the data is useful. Even though multi-spectral imaging would be a beneficial tool for a range of low-cost, real-time, limited-wavelength applications like anticounterfeiting measures or medical diagnostics, the complexity of today's offerings makes it impossible. Multi-spectral imaging has been done by many methods including tunable Liquid Crystal and coated optical filters. In all methods a series of images of differing filtered spectral content are captured over time and then combined into a composite image using a separate computer for processing. This sequence of images is captured slowly and sequentially over time. Examples of prior art are disclosed in U.S. Pat. No. 5,943,129 issued to Hoyt, and U.S. publications 2009/0096895 by Benezra and 2009/0137908 by Patwardhan.
Typically a composite image is generated by various algorithms using spatial data from the sequence of captured images. Any spatial changes (movement) of an object between image captures will result in erroneous data in the composite image. Colors are assigned electronically to the resultant composite image in accordance with an algorithm generally specific to the particular application to enhance or highlight certain spectral information. The invention of this disclosure improves on the prior art by using real time, on-board processing and image stabilization. These improvements allow for simpler construction, lower cost components, and ease of customization for individual applications.